Papers with TAR
Combining Counting Processes and Classification Improves a Stopping Rule for Technology Assisted Review (2023.findings-emnlp)
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| Challenge: | Experiments on multiple data sets show that the proposed approach consistently improves performance and outperforms several alternative methods. |
| Approach: | They propose to integrate a text classifier into an existing TAR stopping rule to train it without the need for additional annotations. |
| Outcome: | Experiments on multiple data sets show the proposed approach outperforms other methods and achieves the desired level of recall with a lower cost than the existing method based on counting processes alone. |
Automatic Spanish Translation of SQuAD Dataset for Multi-lingual Question Answering (2020.lrec-1)
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| Challenge: | Existing methods to train multilingual QA systems are limited for other languages . cross-lingual learning is a technique that transfers knowledge from source to target language with fewer training data. |
| Approach: | They propose a translation method to translate the Stanford Question Answering Dataset to Spanish and a multilingual-BERT model to train Spanish QA systems. |
| Outcome: | The proposed method outperforms the previous benchmarks for cross-lingual extractive QA. |
Beyond Frameworks: Unpacking Collaboration Strategies in Multi-Agent Systems (2025.acl-long)
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| Challenge: | Existing frameworks prioritize structural architectures and role assignments but neglect granular mechanics of agent collaboration. |
| Approach: | They propose to use centralized governance, instructor-led participation, ordered interaction patterns to optimize task accuracy and computational efficiency. |
| Outcome: | The proposed model improves task accuracy and computational efficiency under two context-dependent scenarios. |